Embedded Software Engineer, Edge AI

Every day, companies send their most valuable assets into the world — their people, their equipment, their reputations. For nearly three decades, Lytx has given fleets the tools to manage and protect all the assets they have in motion, helping them stay connected with their field operations so they can focus on delivering value and growing their businesses.

Lytx is building the future of its products on a scalable, cloud-first platform, fusing large-scale AWS infrastructure with the hardware that powers our in-vehicle gateways and smart cameras, plus the AI and fleet services layered on top. We're growing a small, high-output embedded team to build the edge AI behind that: work that directly affects how safely millions of drivers get home each day. Lytx's video telematics devices use machine vision and AI (MV+AI) to turn real-time sensor data into decisions that keep drivers safe — connected to a cloud platform managing a fleet approaching a million devices.

You'll Get To

• Build hands-on skills across the embedded stack. Work in C, C++, and Python across x86 simulation environments and target hardware (Ambarella, Rockchip), with close guidance from senior engineers.
• Contribute to the model pipeline. Help implement defined pieces of the ONNX conversion and pre/post-processing pipeline for existing models (ADAS, DMS), under the direction of a senior engineer who owns the overall design.
• Support the simulation and training environment. Help maintain datasets, training pipelines, and labeling tools, learning how they connect to what ships on-device.
• Learn the system. Get exposure to internal application communication, device-to-device protocols, and device-to-cloud communication over MQTT, and start contributing to small, well-defined pieces of it.
• Grow your debugging and signal-processing skills. Work with senior engineers to understand why a detection succeeded or failed, and take on small, scoped fixes as your understanding grows.
  
  

• 0–2 years of experience in embedded software development (internships and co-ops count).
• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or equivalent experience.
• Working knowledge of C, C++, and Python.
• Exposure to Linux-based systems and comfort learning across hardware platforms.
• A learning mindset — comfortable asking questions and taking direction while building toward independent ownership.
  
  

• Coursework or project experience with computer vision or machine learning.
• Exposure to video pipelines or MP4-based encoding/decoding.
• Familiarity with AI coding tools (e.g., Claude, Gemini) as part of a daily workflow.
  
  

• You won't be handed a fully specified package — you're expected to understand the challenge, propose the solution, and carry it end to end. Small team, fast pace, high ownership.